Summary:
This PR adds Windows support for the C++ frontend. A lot of declarations were missing `TORCH_API` macros, and lots of code just did not compile on MSVC.
ebetica ezyang orionr
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11716
Reviewed By: orionr
Differential Revision: D13038253
Pulled By: goldsborough
fbshipit-source-id: c8e5a45efd26117aeb99e768b56fcd5a89fcb9f8
Summary:
This PR serves two purposes:
1. Design an abstraction over a serialization scheme for C++ modules, optimizers and tensors in general,
2. Add serialization to the ONNX/PyTorch proto format.
This is currently a rough prototype I coded up today, to get quick feedback.
For this I propose the following serialization interface within the C++ API:
```cpp
namespace torch { namespace serialize {
class Reader {
public:
virtual ~Reader() = default;
virtual void read(const std::string& key, Tensor& tensor, bool is_buffer = false) = 0;
virtual void finish() { }
};
class Writer {
public:
virtual ~Reader() = default;
virtual void writer(const std::string& key, const Tensor& tensor, bool is_buffer = false) = 0;
virtual void finish() { }
};
}} // namespace torch::serialize
```
There are then subclasses of these two for (1) Cereal and (2) Protobuf (called the "DefaultWriter" and "DefaultReader" to hide the implementation details). See `torch/serialize/cereal.h` and `torch/serialize/default.h`. This abstraction and subclassing for these two allows us to:
1. Provide a cereal-less serialization forward that we can ship and iterate on going forward,
2. Provide no-friction backwards compatibility with existing C++ API uses, mainly StarCraft.
The user-facing API is (conceptually):
```cpp
void torch::save(const Module& module, Writer& writer);
void torch::save(const Optimizer& optimizer, Writer& writer);
void torch::read(Module& module, Reader& reader);
void torch::read(Optimizer& optimizer, Reader& reader);
```
with implementations for both optimizers and modules that write into the `Writer` and read from the `Reader`
ebetica ezyang zdevito dzhulgakov
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11619
Differential Revision: D9984664
Pulled By: goldsborough
fbshipit-source-id: e03afaa646221546e7f93bb8dfe3558e384a5847
Summary:
I am working on unifying the C++ extensions and C++ API, and one constraint for this is that we will want to be able to build the C++ API without cereal, since we won't want to ship it with the Python `torch` package.
For this I introduce a `TORCH_WITH_CEREAL` option to CMake. If on, the C++ API will be built with cereal and thus serialization support. If off, serialization functions will throw exceptions, but the library will otherwise still compile the same. __This option is on by default, so for regular C++ API users nothing will change__. However, from C++ extensions, we'll be able to turn it off. This effectively means we won't be searching for any cereal headers from C++ API headers, which wouldn't be installed in the Python package.
ebetica ezyang soumith
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11498
Differential Revision: D9784803
Pulled By: goldsborough
fbshipit-source-id: 5d0a1f2501993012d28cf3d730f45932b483abc4
Summary:
Skip torch tests as well when NO_TEST=1 environment variable is set. Also remove the separate ATen code path for not being built with Caffe2, since it will always be built with Caffe2.
cc The controller you requested could not be found.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11415
Reviewed By: soumith
Differential Revision: D9758179
Pulled By: orionr
fbshipit-source-id: e3e3327364fccdc57a703aeaad8c4f30452973fb
Summary:
Take 2 of #10543
The problem was that between commit and merge there was added one more run point `tools/build_libtorch.py`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10659
Differential Revision: D9393540
Pulled By: soumith
fbshipit-source-id: 8ebfed600fc735fd1cb0489b161ec80e3db062e0
Summary:
delete build_caffe2.sh, replace with build_libtorch.py as suggested by peter (and copy-pasted from his draft PR). This ensures that all consumers of the torch CMake file go through as unified a path as possible.
In order to change the surrounding infrastructure as little as possible, I made some tweaks to enable build_pytorch_libs.sh to generate the test binaries relative to the current directory, rather than hardcoding to pytorch/build.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10508
Differential Revision: D9354398
Pulled By: anderspapitto
fbshipit-source-id: 05b03df087935f88fca7ccefc676af477ad2d1e9
